TY - GEN
T1 - Automatic Classification of Lymph Node Metastasis in Non-Small-Cell Lung Cancer (NSCLC) Patient on F-18-FDG PET/CT
AU - Cheng, Tsu Chi
AU - Chiu, Nan Tsing
AU - Fang, Yu Hua
PY - 2020/1/1
Y1 - 2020/1/1
N2 - Lung Cancer is a leading cause of death worldwide, and about 85% of lung cancer is non-small cell lung cancer (NSCLC). The staging of lymph nodes in NSCLC patients is extremely important because respective stages require different treatments. FDG-PET/CT is a gold standard for lymph node metastasis staging of NSCLC. However, the results of discriminating lymph node staging on 18F-2-fluoro-2-deoxy-d-glucose (FDG) positron emission tomography (PET)/computed tomography (CT) still needs improvement. In addition to the traditional image parameters of FDG-PET/CT such as standardized uptake value (SUV), there are many other parameters available from FDG-PET/CT images, for example, the lymphatic drainage pathway. For the purpose of a better accuracy on lymph node metastasis diagnosis on NSCLC patient in FDG-PET/CT, this research developed a computer-aided diagnosis (CAD) system to improve the diagnostic efficiency, which achieved an accuracy of 85%, a sensitivity of 82% and a specificity of 85%.
AB - Lung Cancer is a leading cause of death worldwide, and about 85% of lung cancer is non-small cell lung cancer (NSCLC). The staging of lymph nodes in NSCLC patients is extremely important because respective stages require different treatments. FDG-PET/CT is a gold standard for lymph node metastasis staging of NSCLC. However, the results of discriminating lymph node staging on 18F-2-fluoro-2-deoxy-d-glucose (FDG) positron emission tomography (PET)/computed tomography (CT) still needs improvement. In addition to the traditional image parameters of FDG-PET/CT such as standardized uptake value (SUV), there are many other parameters available from FDG-PET/CT images, for example, the lymphatic drainage pathway. For the purpose of a better accuracy on lymph node metastasis diagnosis on NSCLC patient in FDG-PET/CT, this research developed a computer-aided diagnosis (CAD) system to improve the diagnostic efficiency, which achieved an accuracy of 85%, a sensitivity of 82% and a specificity of 85%.
UR - http://www.scopus.com/inward/record.url?scp=85075806220&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85075806220&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-30636-6_20
DO - 10.1007/978-3-030-30636-6_20
M3 - Conference contribution
AN - SCOPUS:85075806220
SN - 9783030306359
T3 - IFMBE Proceedings
SP - 138
EP - 142
BT - Future Trends in Biomedical and Health Informatics and Cybersecurity in Medical Devices - Proceedings of the International Conference on Biomedical and Health Informatics, ICBHI 2019
A2 - Lin, Kang-Ping
A2 - Magjarevic, Ratko
A2 - de Carvalho, Paulo
PB - Springer
T2 - 4th International Conference on Biomedical and Health Informatics, ICBHI 2019
Y2 - 17 April 2019 through 20 April 2019
ER -